M&A: Sectra Acquires AI Radiology Startup Oxipit to Scale Autonomous Diagnostic Imaging
What You Should Know The Deal: Swedish medical imaging and cybersecurity giant Sectra has entered into an agreement to acquire Oxipit, a Lithuanian startup specializing in AI-based radiology solutions. The deal is expected to close in March 2026. The Tech Shift: While most radiology AI currently acts as a “co-pilot” (flagging findings and acting as ... Read More
<img width="1500" height="784" src="https://hitconsultant.net/wp-content/uploads/2026/03/oxipit-quality-icons-sm-1-1500x784.png" alt="Sectra Acquires AI Radiology Startup Oxipit to Scale Autonomous Diagnostic Imaging" class="wp-image-95010" srcset="https://hitconsultant.net/wp-content/uploads/2026/03/oxipit-quality-icons-sm-1-1500x784.png 1500w, https://hitconsultant.net/wp-content/uploads/2026/03/oxipit-quality-icons-sm-1-300x157.png 300w, https://hitconsultant.net/wp-content/uploads/2026/03/oxipit-quality-icons-sm-1-290x152.png 290w, https://hitconsultant.net/wp-content/uploads/2026/03/oxipit-quality-icons-sm-1-768x401.png 768w, https://hitconsultant.net/wp-content/uploads/2026/03/oxipit-quality-icons-sm-1-1536x803.png 1536w, https://hitconsultant.net/wp-content/uploads/2026/03/oxipit-quality-icons-sm-1-2048x1070.png 2048w" sizes="(max-width: 1500px) 100vw, 1500px" /> What You Should Know The Deal: Swedish medical imaging and cybersecurity giant Sectra has entered into an agreement to acquire Oxipit, a Lithuanian startup specializing in AI-based radiology solutions. The deal is expected to close in March 2026. The Tech Shift: While most radiology AI currently acts as a “co-pilot” (flagging findings and acting as decision support), Oxipit pioneers autonomous AI. Its technology is validated to independently complete specific diagnostic tasks without human intervention. The Flagship Product: Oxipit’s ChestLink holds the world’s first CE Class IIb certification for autonomous AI in chest X-ray analysis. It automatically identifies and clears high-confidence “normal” chest X-rays from the radiologist’s worklist. The Strategic Integration: The Oxipit team will transition into a dedicated AI development center within Sectra’s Imaging IT Solutions division. Meanwhile, Sectra’s Amplifier service will remain an open, vendor-neutral ecosystem for third-party AI applications. From Co-Pilot to Autopilot Imaging volumes are rising globally, while the workforce of trained radiologists is shrinking, leading to massive reporting backlogs. A significant percentage of daily imaging volume—particularly routine chest X-rays—consists of perfectly healthy, “normal” scans. Forcing a highly specialized, highly compensated radiologist to spend hours manually dictating “no acute cardiopulmonary disease” is a massive misallocation of clinical resources. Oxipit’s flagship product, ChestLink, solves this exact bottleneck. Operating under rigorous, validated safety thresholds, ChestLink automatically identifies high-confidence normal chest X-rays and actually clears them from the worklist, finalizing the report without any human intervention. Through the automation of healthy cases, the human radiologist’s queue is instantly enriched with scans that actually require their clinical expertise and judgment. The Regulatory Moat In healthcare AI, the algorithm is only half the battle; the other half is regulatory clearance. Autonomous AI represents an entirely different risk profile than standard Computer-Aided Detection (CAD). ChestLink holds a CE Class IIb certification, which reflects the elevated regulatory and clinical validation standards required to allow a machine to practice medicine independently within the European Economic Area (EEA). By acquiring Oxipit, Sectra isn’t just buying an algorithm; it is buying a highly defensible regulatory moat and a team that has already proven it can navigate the strictest clinical safety standards.
Grow Therapy Secures $150M to Expand Enterprise Partnerships for Mental Health Platform
What You Should Know The Funding: Grow Therapy has secured a $150M Series D led by TCV and Growth Equity at Goldman Sachs Alternatives with new participation from BCI and Menlo Ventures, the round brings Grow’s total capital raised to $328M at a reported $3 billion valuation. The Scale: The company has quietly built a ... Read More
<img loading="lazy" width="1500" height="399" src="https://hitconsultant.net/wp-content/uploads/2026/03/GrowTherapy-1500x399.jpg" alt="Grow Therapy Secures $150M to Expand Enterprise Partnerships for Mental Health Platform" class="wp-image-95006" srcset="https://hitconsultant.net/wp-content/uploads/2026/03/GrowTherapy-1500x399.jpg 1500w, https://hitconsultant.net/wp-content/uploads/2026/03/GrowTherapy-300x80.jpg 300w, https://hitconsultant.net/wp-content/uploads/2026/03/GrowTherapy-290x77.jpg 290w, https://hitconsultant.net/wp-content/uploads/2026/03/GrowTherapy-768x204.jpg 768w, https://hitconsultant.net/wp-content/uploads/2026/03/GrowTherapy-1536x408.jpg 1536w, https://hitconsultant.net/wp-content/uploads/2026/03/GrowTherapy.jpg 2042w" sizes="(max-width: 1500px) 100vw, 1500px" /> What You Should Know The Funding: Grow Therapy has secured a $150M Series D led by TCV and Growth Equity at Goldman Sachs Alternatives with new participation from BCI and Menlo Ventures, the round brings Grow’s total capital raised to $328M at a reported $3 billion valuation. The Scale: The company has quietly built a massive footprint, reaching a reported $1 billion revenue run rate. In 2025 alone, Grow facilitated 7 million visits, connecting its 26,000 providers with patients across 125+ health insurer partners. The “EAP Cliff” Solution: Grow is officially entering the employer benefits space by redesigning the traditional Employee Assistance Program (EAP). Instead of employees maximizing their 3 to 5 free EAP sessions and being forced to switch therapists, Grow’s platform allows a seamless transition to the employee’s standard health insurance, keeping the same provider. The AI Leverage: To attract and retain its massive provider network, Grow deployed a free, clinically-guided AI notetaker that has successfully slashed provider documentation time by nearly 70%. The Primary Care Bridge: Grow is extending its platform directly into health systems—beginning with Circle Medical—to coordinate referrals and ensure patients screened for mental health issues in primary care actually make it to treatment. Eradicating the “EAP Cliff” For decades, corporate mental health benefits have been functionally broken. Employers typically offer an Employee Assistance Program (EAP) that grants workers a handful of free therapy sessions. However, EAPs and traditional health insurance networks are almost never connected. When an employee inevitably exhausts their 3 to 5 free EAP sessions, they hit a “cliff.” They are forced to either pay exorbitant out-of-pocket cash rates to stay with their therapist, or abruptly end their care and start over with a new, in-network provider. Grow Therapy is using its new enterprise expansion to kill this cliff. Beginning in March 2026, companies can offer Grow Therapy through a redesigned benefit program that bridges the gap. Because Grow already has deep integrations with over 125 health insurers (covering 220 million lives, including Medicare and Medicaid), an employee can seamlessly transition from their EAP directly to their standard health insurance—without ever changing their therapist. Furthermore, Grow is offering a highly attractive pricing model for CFOs: they only charge employers for the care actually delivered, abandoning the wasteful, flat Per-Member-Per-Month (PMPM) fees that plague traditional digital health contracts. Automating the Administrative Grind You cannot scale a mental health network to 7 million annual visits without an army of providers. And the only way to attract 26,000 independent providers in a massive clinical shortage is to build software that makes their lives easier. Administrative burnout is the primary enemy of the independent therapist. To combat this, Grow introduced a free, clinically-guided AI notetaker natively embedded into its EHR software. By ambiently capturing the session and structuring the clinical documentation, the AI tool has dropped provider documentation time by nearly 70%, surpassing the accuracy of manual note-taking. This operational leverage allows therapists to see more patients, drives 80% of clients to see measurable symptom improvement within 30 days, and yields a world-class Net Promoter Score (NPS) of 85. Bridging the Primary Care Chasm While employers control the purse strings, primary care doctors control the funnel. Annually, more than 70% of people receive a mental health screening during a routine medical visit, but less than half actually make their way to treatment. The referral process is simply too fragmented. To fix this, Grow is extending its platform directly into health systems, starting with national primary care company Circle Medical. Medical teams can now coordinate referrals, share clinical context with patient consent, and schedule the first therapy session directly within their existing workflows.
Elation Health Launches AI Fast Lane to Automate Primary Care Billing Workflows
What You Should Know The Launch: Elation Health, a clinical-first technology platform for primary care, has launched new AI-powered billing workflows featuring a “touchless fast lane” for claims. The Hard ROI: In pilot practices, 72% of eligible routine claims were created completely touchlessly directly from the visit note sign-off. Of those, over 95% were reviewed, ... Read More
<img loading="lazy" width="1215" height="648" src="https://hitconsultant.net/wp-content/uploads/2026/03/AI-Billing-Elation-Health.jpg" alt="Elation Health Launches AI Fast Lane to Automate Primary Care Billing Workflows" class="wp-image-95014" srcset="https://hitconsultant.net/wp-content/uploads/2026/03/AI-Billing-Elation-Health.jpg 1215w, https://hitconsultant.net/wp-content/uploads/2026/03/AI-Billing-Elation-Health-300x160.jpg 300w, https://hitconsultant.net/wp-content/uploads/2026/03/AI-Billing-Elation-Health-290x155.jpg 290w, https://hitconsultant.net/wp-content/uploads/2026/03/AI-Billing-Elation-Health-768x410.jpg 768w" sizes="(max-width: 1215px) 100vw, 1215px" /> What You Should Know The Launch: Elation Health, a clinical-first technology platform for primary care, has launched new AI-powered billing workflows featuring a “touchless fast lane” for claims. The Hard ROI: In pilot practices, 72% of eligible routine claims were created completely touchlessly directly from the visit note sign-off. Of those, over 95% were reviewed, confirmed, and submitted for reimbursement without any additional manual intervention. Smart Coding in the Encounter: The AI utilizes context already in the Elation EHR—such as pre-visit details, AI-drafted visit notes (Note Assist), problem lists, and medications—to proactively suggest complete diagnosis, procedure, and drug codes before a bill is even generated. The Fast Lane Mechanics: Claims are checked against coverage and billing rules. If they meet a pre-defined confidence threshold set by the practice, they are routed into a touchless fast lane for submission. Complex exceptions are held back and clearly flagged for human review. The Financial Benchmarks: The architecture is designed to drive practices toward elite revenue cycle metrics: denial rates under 5% and first-pass paid rates above 95%. How the “Fast Lane” Actually Works Historically, EHRs and billing software operated as two separate silos. The doctor wrote the note, and then a biller (or the doctor themselves, working after hours) had to translate that clinical narrative into a complex series of CPT and ICD-10 codes. Elation’s new system bridges this gap through Smart Coding. The AI scans the pre-visit details, the patient’s problem list, active medications, and the visit note itself (often drafted by Elation’s ambient AI scribe, Note Assist). It then proactively suggests the correct diagnosis, procedure, and drug codes. The workflow shifts from building a claim from scratch to simply confirming the AI’s highly educated guess. Once confirmed, the system checks the claim against coverage rules. If the claim hits a pre-defined confidence threshold, it bypasses the manual review queue and enters the “touchless fast lane” for immediate submission. The early metrics are staggering. In pilot programs, 72% of eligible routine claims were created touchlessly. Out of that cohort, more than 95% were submitted without a single additional manual keystroke. Curing the “Two-Job” Syndrome The ultimate value of this technology isn’t just a lower Days in Accounts Receivable (A/R) metric—though Elation is targeting elite benchmarks like a sub-5% denial rate and a >95% first-pass paid rate. The real value is the restoration of the clinician’s time and sanity. “Reimbursement for delivering primary care shouldn’t be this hard,” said Kyna Fong, CEO and co‑founder of Elation Health. “Elation’s approach is simple: billing should support great care, not get in the way of it. With these new fast lane workflows, we’re moving closer to a world where clinicians see the patient, the clinical story of the visit is captured for them in the chart, and the administrative busywork happens quietly in the background.”
Mayo Clinic Platform_Accelerate Announces Latest Cohort of 18 Digital Health Companies
What You Should Know The Announcement: Mayo Clinic Platform_Accelerate has officially welcomed its newest cohort, selecting 18 national and international healthcare technology companies to participate in its 30-week immersive program. The “Moat”: The most significant benefit of the program is access to Mayo Clinic’s data ecosystem. Startups will be able to utilize millions of de-identified, ... Read More
<img loading="lazy" width="1500" height="843" src="https://hitconsultant.net/wp-content/uploads/2026/03/Mayo-Clinic-Platform_Accelerate-1500x843.webp" alt="Mayo Clinic Platform_Accelerate Announces Latest Cohort of 18 Digital Health Companies" class="wp-image-94995" srcset="https://hitconsultant.net/wp-content/uploads/2026/03/Mayo-Clinic-Platform_Accelerate-1500x843.webp 1500w, https://hitconsultant.net/wp-content/uploads/2026/03/Mayo-Clinic-Platform_Accelerate-300x169.webp 300w, https://hitconsultant.net/wp-content/uploads/2026/03/Mayo-Clinic-Platform_Accelerate-290x163.webp 290w, https://hitconsultant.net/wp-content/uploads/2026/03/Mayo-Clinic-Platform_Accelerate-768x432.webp 768w, https://hitconsultant.net/wp-content/uploads/2026/03/Mayo-Clinic-Platform_Accelerate-1536x864.webp 1536w, https://hitconsultant.net/wp-content/uploads/2026/03/Mayo-Clinic-Platform_Accelerate.webp 1921w" sizes="(max-width: 1500px) 100vw, 1500px" /> What You Should Know The Announcement: Mayo Clinic Platform_Accelerate has officially welcomed its newest cohort, selecting 18 national and international healthcare technology companies to participate in its 30-week immersive program. The “Moat”: The most significant benefit of the program is access to Mayo Clinic’s data ecosystem. Startups will be able to utilize millions of de-identified, longitudinal clinical records to develop, train, and validate their artificial intelligence (AI) models. The Clinical Scope: The 18 selected companies cover a massive swath of clinical and operational needs, ranging from genomic cancer diagnostics and rare disease therapies to AI-powered surgical navigation and GLP-1 obesity care management. The Cohort: From the Front Desk to the Operating Room For 30 weeks, these startups will not only receive expert mentorship from Mayo Clinic clinicians, but they will also be granted the golden ticket of health-tech: access to millions of de-identified, longitudinal clinical records to validate and refine their AI-driven solutions. The selected companies highlight the industry’s shift away from generic AI chatbots and toward highly specialized, multimodal clinical applications. The 18 startups can be broadly categorized into several key domains: 1. Precision Medicine & Oncology Curenetics: A U.K.-based company integrating clinical, genomic, and imaging data to predict how individual patients will respond to cancer immunotherapy. Xcoo: Provides an AI-powered service (Chrovis) that supports genomic cancer diagnosis and treatment decisions. Ecotone AI: Applies frontier AI and full-genome analysis to uncover disease-driving genetic mechanisms for rare diseases. 2. Surgical Intelligence & Acute Care Precision Imaging Inc: A Tokyo-based medtech startup using computer vision for high-precision, intraoperative navigation in orthopedic surgeries (starting with hip arthroplasty). Bluevia Health: An applied AI platform that analyzes multimodal clinical data to detect postoperative deterioration earlier. Hoopcare: Automates preoperative evaluations and predicts postoperative complications to reduce surgical risk. NeoCure Inc: Analyzes bedside vital data to detect eye diseases in preterm infants without requiring an on-site specialist. 3. Chronic Care, GLP-1s & Fertility EW2Health: Uses predictive behavioral analytics to forecast weight trends and enable proactive interventions for patients utilizing GLP-1 therapies. Canary Applied Intelligence: Identifies high-risk patients in cardio-renal care to enable proactive interventions. YOBO Health: A care coordination platform designed to prevent hospital readmissions for cardio-renal-metabolic conditions. Hera: Combines testing with predictive analytics to deliver personalized sperm health insights for male fertility. OneMedic: A Vietnam-based primary care ecosystem using AI for early detection and management of chronic diseases. NousLogic Telehealth: A remote elderly patient monitoring platform that tracks vital signs and includes AI-based medication dispensing. MyBackHub: Uses AI to triage and guide personalized, nonoperative back pain care. 4. Administrative & Operational Automation 100ms: Builds AI agents that automate patient access workflows for specialty practices. SPRYT: Develops “Asa,” an AI medical receptionist that empowers patients to book and pay for appointments via text in their preferred language. Avedian: Delivers operational insights to help health systems improve efficiency and capacity planning. Cura AI: Unifies fragmented data into a portable, patient-owned record to support early-risk detection. “The innovation we’re seeing in this February cohort is a testament to the accelerating pace of AI in medicine,” said Jamie Sundsbak, director of the Accelerate program. “We are proud to support these 18 companies as they transition from revolutionary concepts to scalable solutions that can help define the next decade of healthcare.”
Why Pharma Must Adopt “Decision Engines” for Medical Engagement
Pharma medical affairs teams have spent the last decade investing heavily in digital transformation. Virtual advisory boards, omnichannel platforms, CRM systems, and analytics dashboards are now standard. Yet despite this progress, many medical engagement strategies still appear static. Plans are often locked in annually, channels are treated as separate silos, and success is measured by ... Read More
<img loading="lazy" src="https://hitconsultant.net/wp-content/uploads/2026/03/Jones-Jaick_Headshot-1-1500x1875.jpg" alt="" class="wp-image-94878" width="457" height="571" srcset="https://hitconsultant.net/wp-content/uploads/2026/03/Jones-Jaick_Headshot-1-1500x1875.jpg 1500w, https://hitconsultant.net/wp-content/uploads/2026/03/Jones-Jaick_Headshot-1-240x300.jpg 240w, https://hitconsultant.net/wp-content/uploads/2026/03/Jones-Jaick_Headshot-1-232x290.jpg 232w, https://hitconsultant.net/wp-content/uploads/2026/03/Jones-Jaick_Headshot-1-768x960.jpg 768w, https://hitconsultant.net/wp-content/uploads/2026/03/Jones-Jaick_Headshot-1-1229x1536.jpg 1229w, https://hitconsultant.net/wp-content/uploads/2026/03/Jones-Jaick_Headshot-1-1638x2048.jpg 1638w, https://hitconsultant.net/wp-content/uploads/2026/03/Jones-Jaick_Headshot-1-scaled.jpg 2048w" sizes="(max-width: 457px) 100vw, 457px" /> Jones Jaick, Partner at ZS Associates Pharma medical affairs teams have spent the last decade investing heavily in digital transformation. Virtual advisory boards, omnichannel platforms, CRM systems, and analytics dashboards are now standard. Yet despite this progress, many medical engagement strategies still appear static. Plans are often locked in annually, channels are treated as separate silos, and success is measured by activity rather than relevance. The disconnect is not a lack of data or tools. It is that engagement models have not kept pace with how healthcare professionals actually consume scientific information today. In a world where clinicians move fluidly between formats, timelines, and levels of depth, static engagement plans struggle to remain useful. Decision engines help bridge that gap by shifting medical affairs from rigid execution to adaptive, insight-guided engagement that respects both scientific integrity and regulatory boundaries. Why static engagement no longer reflects how HCPs learn Medical affairs planning has traditionally mirrored clinical trial thinking. You define objectives, map audiences, select channels, and execute against a fixed plan. This approach works well in controlled environments. It works far less well in the reality of modern clinical practice. Today, a single healthcare professional may skim a congress highlight on a mobile device between patients, attend a virtual symposium weeks later, download a publication when a complex case arises, and engage with an MSL months after that. Their needs change based on specialty, patient mix, time pressure, and evolving evidence. Static engagement models assume predictability where there is none. This is akin to prescribing the same treatment plan for every patient, regardless of symptoms or disease progression. In medicine, personalization is non-negotiable. In medical engagement, it remains aspirational. Let us take spectrum allocation as an example. Spectrum allocation illustrates the difference between static and adaptive decision-making. Fixed assignments can work in stable conditions, but interference, demand spikes, or new devices quickly create problems. Modern systems dynamically adjust frequencies within regulatory guardrails, shifting usage where needed while preventing conflicts. Adaptive frameworks balance flexibility and control, maintaining reliability and trust even in complex, changing environments When engagement plans are fixed and channel-specific, teams risk either overcommunicating or missing the moment when information is most valuable. Scientific exchange becomes transactional rather than contextual. The result is frustration on both sides, with medical teams executing plans that feel compliant but not necessarily helpful. Decision engines as navigational systems, not automation shortcuts Decision engines are often misunderstood as tools that automate engagement or replace human judgment. In medical affairs, their real value lies elsewhere. They function more like navigational systems than autopilots. A navigation app does not decide where you should go. It helps you choose the best route based on traffic, timing, and constraints. Similarly, a decision engine can help medical teams determine when engagement is appropriate, which content is relevant, and which channel aligns with the current context, while leaving final judgment to medical professionals. Rather than pre-assigning fixed touchpoints, decision engines synthesize signals such as prior interactions, content consumption patterns, specialty-specific behaviors, and external events like congresses or guideline updates. This allows teams to respond to real-world behavior rather than forcing behavior into predefined plans. Importantly, this does not mean chasing every signal. In regulated environments, restraint matters as much as responsiveness. A well-designed decision engine operates within guardrails that reflect compliance rules, scientific standards, and approved content. It guides choices, it does not improvise them. A useful analogy is how traffic management or mobility systems operate in the real world. Traffic moves unconstrained. Clear rules and considerations are applied in regulating traffic and managing congestion through signals, lanes, and speed limits that balance traffic flow with predictability. By shifting the focus from channel execution to decision quality, medical affairs teams can support scientific exchange that feels timely and relevant without crossing regulatory lines. Engagement becomes less about volume and more about appropriateness. What pharma leaders need to make adaptive engagement work Moving from static plans to intelligent engagement is not primarily a technology challenge. It is an organizational one. Decision engines only work when certain capabilities are in place. First, data must be connected across touchpoints. Fragmented systems lead to fragmented decisions. Leaders need to prioritize interoperability and shared definitions of engagement success, not just more dashboards. Second, governance models must evolve. Adaptive engagement requires clarity on what decisions can be guided by algorithms and which require human oversight. Medical, legal, and compliance teams need to be involved early, not as gatekeepers at the end. Third, medical teams need confidence and training. Decision engines should empower MSLs and medical leaders, not constrain them. This means investing in change management and reinforcing that professional judgment remains central. Finally, leadership must accept that adaptive engagement looks messier than static plans. Outcomes may be harder to predict, but they are often more meaningful. Just as personalized medicine embraces variability to improve patient outcomes, intelligent medical engagement embraces flexibility to improve scientific exchange. As digital transformation matures, the question is no longer whether pharma has the tools to engage differently. It is whether medical affairs organizations are willing to rethink how decisions are made. Decision engines offer a path forward not by automating science but by enabling smarter, more human engagement in an increasingly complex information landscape. About Jones Jaick Jones Jaick leads global medical digital and omnichannel transformation initiatives, helping life sciences organizations improve their engagement through strategy, technology, and analytics. A Partner at ZS Associates, he works across medical engagement, decision engines, omnichannel strategy, and customer data foundations. He has partnered with medical affairs teams across the US and international markets and has spoken at industry events including MAPS, DIA MASC, and Reuters.
LexisNexis Brings Deepfake and Fraud Defense to Epic MyChart
What You Should Know The Integration: LexisNexis Risk Solutions is significantly expanding its footprint within the Epic Connection Hub, allowing U.S. hospitals using Epic to natively deploy a broader suite of identity verification tools. The Target: The primary goal is to secure access to Epic MyChart, ensuring that only successfully verified patients can access their ... Read More
<img loading="lazy" width="600" height="181" src="https://hitconsultant.net/wp-content/uploads/2026/03/324390_LexisNexis_Risk_Solutions_Logo_1yHighv1.jpg" alt="LexisNexis Brings Deepfake and Fraud Defense to Epic MyChart" class="wp-image-94997" srcset="https://hitconsultant.net/wp-content/uploads/2026/03/324390_LexisNexis_Risk_Solutions_Logo_1yHighv1.jpg 600w, https://hitconsultant.net/wp-content/uploads/2026/03/324390_LexisNexis_Risk_Solutions_Logo_1yHighv1-300x91.jpg 300w, https://hitconsultant.net/wp-content/uploads/2026/03/324390_LexisNexis_Risk_Solutions_Logo_1yHighv1-290x87.jpg 290w" sizes="(max-width: 600px) 100vw, 600px" /> What You Should Know The Integration: LexisNexis Risk Solutions is significantly expanding its footprint within the Epic Connection Hub, allowing U.S. hospitals using Epic to natively deploy a broader suite of identity verification tools. The Target: The primary goal is to secure access to Epic MyChart, ensuring that only successfully verified patients can access their highly sensitive personal health information (PHI) while maintaining a frictionless user experience. The Tech Stack: The expanded portfolio gives health systems modular access to tools like ThreatMetrix (an AI-powered behavioral and device risk platform), Flex ID, Phone Finder, and One Time Password (OTP) authenticators. The Roadmap: LexisNexis announced future plans to integrate IDVerse, an AI‑powered verification solution that uses biometric and document authentication to detect deepfakes and forgeries, supporting a dynamic, NIST IAL2-certified workflow. A Modular Approach to Identity Risk The power of this integration lies in its modularity. Because the tools integrate seamlessly with Epic, hospital IT teams can dynamically choose which components of the LexisNexis suite they want to combine based on their specific risk tolerance. Instead of relying solely on easily compromised passwords, health systems can deploy a layered defense: Passive Behavioral Analytics: Using LexisNexis ThreatMetrix, hospitals can deploy AI to analyze user behavior, device characteristics, and transaction patterns in the background. If a patient logs in from their usual iPhone in their home zip code, the friction remains low. If a login attempt occurs from an unrecognized device halfway across the globe, the system flags it as a potential fraudster. Active Verification: For higher-risk scenarios, hospitals can trigger tools like Instant Verify to validate self-provided identity information, or leverage Phone Finder and One Time Password (OTP) solutions to ensure the user actually possesses the device tied to the account. IDVerse Integration with Epic LexisNexis confirmed plans to integrate IDVerse into the Epic framework. As generative AI makes it trivially easy for scammers to create synthetic identities, forged driver’s licenses, and deepfake videos, legacy identity verification will soon be obsolete. LexisNexis will deploy AI-powered document and biometric authentication directly into the MyChart onboarding flow. Together, LexisNexis and Epic are future-proofing the digital front door against the next generation of automated cybercrime. “In an industry that remains a top target for cybercrime, striking a balance between user experience and security is critical,” said Jonathan Shannon, AVP of healthcare strategy at LexisNexis Risk Solutions. “This integration is another step forward in instilling confidence and trust in healthcare organizations and patients alike.”
Thyme Care Launches Integrated Social Support (ISS) Model Powered by AI Acuity Engine
What You Should Know The Launch: Thyme Care, a leading value-based cancer care enabler, has officially launched its Integrated Social Support (ISS) model. The Paradigm Shift: Instead of waiting for a patient to flag an emotional or financial crisis, Thyme Care is positioning licensed, master’s-level social workers as the first point of intervention. 100% of ... Read More
<img loading="lazy" width="1280" height="591" src="https://hitconsultant.net/wp-content/uploads/2026/03/Thyme_Care_Logov1.jpg" alt="Thyme Care Launches Integrated Social Support (ISS) Model Powered by AI Acuity Engine" class="wp-image-94996" srcset="https://hitconsultant.net/wp-content/uploads/2026/03/Thyme_Care_Logov1.jpg 1280w, https://hitconsultant.net/wp-content/uploads/2026/03/Thyme_Care_Logov1-300x139.jpg 300w, https://hitconsultant.net/wp-content/uploads/2026/03/Thyme_Care_Logov1-290x134.jpg 290w, https://hitconsultant.net/wp-content/uploads/2026/03/Thyme_Care_Logov1-768x355.jpg 768w" sizes="(max-width: 1280px) 100vw, 1280px" /> What You Should Know The Launch: Thyme Care, a leading value-based cancer care enabler, has officially launched its Integrated Social Support (ISS) model. The Paradigm Shift: Instead of waiting for a patient to flag an emotional or financial crisis, Thyme Care is positioning licensed, master’s-level social workers as the first point of intervention. 100% of members are proactively screened for psychosocial barriers at enrollment. The Data Reality: Proactive screening at just one partner site revealed staggering non-clinical barriers: 53% of patients faced financial toxicity, 22% experienced food insecurity, and 13% had transportation barriers. The AI Engine: The human-led social work team is powered by a proprietary AI infrastructure that continuously synthesizes claims, clinical, and social data into a “dynamic acuity model.” This algorithm ensures the highest-risk patients are prioritized for outreach in real time. Scaling Empathy with AI In healthcare operations, the primary challenge with social work is scalability. How do you deploy highly trained clinical social workers (LCSWs) efficiently across a massive, geographically dispersed patient population without burning them out? Thyme Care solves this by wrapping its human workforce in a layer of advanced data architecture. The company’s social work team is directed by an AI infrastructure that continuously ingests and synthesizes claims data, clinical records, and social determinants of health (SDOH) metrics. This data feeds a dynamic “acuity model” that triages the patient panel in real time. Instead of working blindly through a static list of phone numbers, the technology ensures that Thyme Care’s social workers are instantly routed to the patients whose data signals an impending crisis, ensuring nobody slips through the cracks. ISS Model Clinical and Financial ROI When you combine intelligent tech routing with proactive human screening (utilizing validated tools like the NCCN Distress Thermometer and the Columbia Suicide Risk Assessment), the financial and clinical ROI materializes rapidly. Since introducing ISS in late 2025, Thyme Care has scaled its team to over 40 licensed master-level social workers, making it one of the largest value-based oncology social work investments in the country. The results are undeniable: High-risk members engaged in symptom monitoring experience a 30% relative risk reduction in ED or inpatient events. Members completing discharge assessments see a 20% relative risk reduction in hospital readmissions. 88% of members report feeling more supported after engaging with the platform. Once a barrier is identified, the ISS model deploys targeted interventions, ranging from virtual peer support groups and 12-week self-guided educational programs to one-on-one crisis intervention and behavioral health stabilization. “You cannot treat cancer without addressing the emotional and social realities that come with it,” said Stephanie Broussard, DSW, LCSW-S, APHSW-C, Director of Social Work at Thyme Care. “In five years of supporting individuals with cancer, Thyme Care has continuously iterated on this belief, and what we’ve learned is that the barriers most likely to derail treatment are rarely clinical. Social workers are trained to look beyond the presenting problem and understand the why behind it, whether that’s housing instability, caregiver strain, depression, or fear about the future. There isn’t a shortage of social workers; there’s a shortage of intention. We’ve intentionally built a model that centers their expertise from the very beginning, so we can identify needs earlier and truly support the whole person.”
Why Guideway Care Acquired Waypoint to Fix the EHR Execution Gap
What You Should Know The Deal: Guideway Care, a leader in evidence-based patient activation, has acquired and integrated Waypoint Healthcare Solutions. Waypoint’s entire team, including founders Lisa McDermott and David Bradshaw, has joined Guideway. The Core Problem: Health systems have invested heavily in Electronic Health Records (EHRs), digital front doors, and population health analytics. However, ... Read More
<img loading="lazy" width="400" height="278" src="https://hitconsultant.net/wp-content/uploads/2026/03/guideway-care.jpg" alt="" class="wp-image-94992" srcset="https://hitconsultant.net/wp-content/uploads/2026/03/guideway-care.jpg 400w, https://hitconsultant.net/wp-content/uploads/2026/03/guideway-care-300x209.jpg 300w, https://hitconsultant.net/wp-content/uploads/2026/03/guideway-care-290x202.jpg 290w" sizes="(max-width: 400px) 100vw, 400px" /> Guideway Care, the Patient Activation Company What You Should Know The Deal: Guideway Care, a leader in evidence-based patient activation, has acquired and integrated Waypoint Healthcare Solutions. Waypoint’s entire team, including founders Lisa McDermott and David Bradshaw, has joined Guideway. The Core Problem: Health systems have invested heavily in Electronic Health Records (EHRs), digital front doors, and population health analytics. However, a massive “execution gap” remains in the non-clinical layer. Identifying a social determinant of health (SDoH) or logging a referral in the EHR does not guarantee the patient will actually book the appointment, leading to revenue leakage and poor value-based care performance. The Technology Strategy: Waypoint brings specialized AI and virtual agent tools to the table. Rather than pitching AI as a standalone automation product that replaces staff, Guideway is utilizing it as an “amplification layer.” AI handles real-time detection, pattern recognition, and scalable orchestration, empowering human Activation Specialists to focus on contextual judgment and empathy. The RCM Impact: By governing the execution layer between encounters, the unified platform aims to directly improve the revenue cycle through increased referral closure, reduced avoidable emergency department utilization, and gap closure for at-risk populations. Moving from Engagement to Activation For years, digital health vendors have sold “patient engagement” tools—usually manifesting as generic SMS blasts or passive patient portals. But engagement is not execution. Guideway Care is pivoting the industry toward “Patient Activation.” The difference is measurable completion. It is the discipline of ensuring that high-intent digital access demand actually converts into a scheduled visit, or that diagnostic findings don’t decay in the space between clinical encounters. “For years, the biggest barrier to delivering measurable clinical and financial outcomes has not been effort or investment — it has been effective execution,” said David Bradshaw, now CEO of Waypoint. “Healthcare has no shortage of strategy or technology. What it lacks are proven solutions that ensure the next right step is completed at scale. AI as an Amplification Layer The most compelling aspect of this acquisition is how the combined entity views artificial intelligence. In the current health-tech hype cycle, AI is frequently pitched as a standalone automation tool designed to replace human labor. Guideway is taking a much more pragmatic, effective approach. Waypoint brings advanced AI and virtual agent tools that serve as an “amplification layer” within a governed ecosystem. The AI handles the heavy lifting of real-time risk detection, pattern recognition, and scalable workflow orchestration. This prevents patients from slipping through the cracks. But when a patient hits a complex logistical or emotional barrier, the system seamlessly routes them to a human Activation Specialist. The technology handles the scale; the human handles the relational continuity and empathy. “Healthcare payers and providers have invested heavily in electronic health records, digital front doors, nurse triage platforms, population health analytics, and enterprise AI,” said Craig Parker, Chief Executive Officer of Guideway Care. “Yet enterprise performance still depends on whether patients or members complete the right actions at the right time. The addition of Waypoint’s team and technology gives us additional AI and virtual agent tools to expand our reach and improve our efficiency while allowing us to tailor every interaction to each patient’s preferred activation pathway. Together, we now deliver a unified and integrated Activation Intelligence solution that connects payer and provider strategy directly to measurable completion across access, referral management, care transitions, chronic condition management, and enterprise growth,” Parker added.
AWS Announces Amazon Connect Health: Agentic AI for Clinical Workflows and Scheduling
What You Should Know The Launch: AWS has officially launched Amazon Connect Health, the company’s first purpose-built, agentic AI solution designed specifically for healthcare providers and their patients. The Capability: The platform acts as an autonomous administrative workforce, integrating directly with existing Electronic Health Records (EHRs) to handle patient verification, appointment scheduling, medical history reviews, ... Read More
<img loading="lazy" width="1200" height="823" src="https://hitconsultant.net/wp-content/uploads/2026/03/image-6.png" alt="AWS Announces Amazon Connect Health: Agentic AI for Clinical Workflows and Scheduling" class="wp-image-95003" srcset="https://hitconsultant.net/wp-content/uploads/2026/03/image-6.png 1200w, https://hitconsultant.net/wp-content/uploads/2026/03/image-6-300x206.png 300w, https://hitconsultant.net/wp-content/uploads/2026/03/image-6-290x199.png 290w, https://hitconsultant.net/wp-content/uploads/2026/03/image-6-768x527.png 768w" sizes="(max-width: 1200px) 100vw, 1200px" /> What You Should Know The Launch: AWS has officially launched Amazon Connect Health, the company’s first purpose-built, agentic AI solution designed specifically for healthcare providers and their patients. The Capability: The platform acts as an autonomous administrative workforce, integrating directly with existing Electronic Health Records (EHRs) to handle patient verification, appointment scheduling, medical history reviews, clinical documentation, and medical coding. The Clinical Workflow: Amazon Connect Health operates across the entire care continuum. It surfaces patient history summaries before the visit, ambiently transcribes notes during the visit, and generates billing-ready medical codes after the visit. The Early Traction: Early adopters are seeing massive ROI. UC San Diego Health reported diverting 630 hours weekly from routine patient verification to direct assistance, slashing call abandonment rates by 30%. Meanwhile, Amazon-owned One Medical has already utilized the ambient documentation features across more than a million visits. The Trust Engine: To ensure clinical safety, AWS utilizes “evidence mapping”—a feature that links every piece of AI-generated output (like a medical code or clinical summary) back to the exact moment in the transcript or medical record where it was sourced, allowing for rapid, confident human auditing. Agentic AI: Beyond Passive Chatbots Unlike standard generative AI that simply answers text prompts, “agentic” AI can autonomously execute multi-step workflows across different software platforms. Amazon Connect Health integrates directly with the Electronic Health Records (EHRs) that clinicians already use. When a patient calls and says, “I want to see my doctor after work next week,” the AI agent understands the context. It verifies the patient’s identity, checks their insurance eligibility, cross-references provider availability in the EHR, and books the appointment—all while the patient is still on the line, in natural language, 24/7. When a situation requires human nuance or clinical judgment, the AI seamlessly escalates the call to human staff, complete with a real-time summary of the interaction so the patient never has to repeat themselves. The operational leverage here is staggering. UC San Diego Health, which processes 3.2 million patient interactions annually, deployed the technology and immediately saved 1 minute per call, diverting 630 hours weekly from manual patient verification to actual patient assistance. Automating the Clinical Encounter Amazon Connect Health’s ambitions extend far beyond the contact center; the AI is designed to flank the clinician throughout the entire visit. Before the Visit: The AI synthesizes the patient’s fragmented medical history across care settings, surfacing a concise briefing on active conditions, recent events, and care gaps. During the Visit: With patient consent, the AI ambiently transcribes the doctor-patient conversation and drafts clinical notes in real time. After the Visit: The platform generates patient-friendly visit summaries and suggests the specific medical codes required for billing. Visits become billing-ready in minutes rather than days. The “Evidence Mapping” Imperative The healthcare industry is rightfully skeptical of AI “hallucinations.” To build trust, AWS engineered the platform around transparency through a feature called evidence mapping. If the AI drafts a clinical note stating “patient reports poor diet,” or suggests a specific billing code, the clinician can click on that output and be taken directly to the exact moment in the audio transcript or the specific line in the medical record where that information originated. This allows providers to audit, refine, and submit AI-generated work with total confidence.
Microsoft Upgrades Dragon Copilot to an Agentic Clinical Assistant at HIMSS 2026
What You Should Know: The Evolution: At HIMSS 2026, Microsoft announced that Dragon Copilot is evolving from a standalone ambient documentation tool into a unified AI clinical assistant. It now integrates with Microsoft 365 Copilot, allowing clinicians to pull work-related context (emails, chats, schedules) directly into the clinical workflow. Microsoft revealed that more than 100,000 ... Read More
<img loading="lazy" width="900" height="456" src="https://hitconsultant.net/wp-content/uploads/2026/03/Dragon-Copilot.jpg" alt="" class="wp-image-94986" srcset="https://hitconsultant.net/wp-content/uploads/2026/03/Dragon-Copilot.jpg 900w, https://hitconsultant.net/wp-content/uploads/2026/03/Dragon-Copilot-300x152.jpg 300w, https://hitconsultant.net/wp-content/uploads/2026/03/Dragon-Copilot-290x147.jpg 290w, https://hitconsultant.net/wp-content/uploads/2026/03/Dragon-Copilot-768x389.jpg 768w" sizes="(max-width: 900px) 100vw, 900px" /> What You Should Know: The Evolution: At HIMSS 2026, Microsoft announced that Dragon Copilot is evolving from a standalone ambient documentation tool into a unified AI clinical assistant. It now integrates with Microsoft 365 Copilot, allowing clinicians to pull work-related context (emails, chats, schedules) directly into the clinical workflow. Microsoft revealed that more than 100,000 clinicians currently rely on Dragon Copilot as part of their daily practice, supporting the care of millions of patients every month. The “App Store” Model: Microsoft has opened Dragon Copilot to third-party innovation via the Microsoft Marketplace. Health systems can now deploy partner-built AI apps and agents (from companies like Canary Speech, Optum, and Regard) directly inside the Copilot interface to handle tasks like revenue cycle management and prior authorization. Role-Specific Expansion: Microsoft is moving aggressively beyond the physician. The platform now includes deeply tailored workflows for nurses (automating structured flowsheet entries like med-surg and line insertions) and radiologists (paired with PowerScribe One to summarize prior reports). Global Footprint: The physician experience for Dragon Copilot has expanded internationally and is now available in the U.S., Canada, the UK, Ireland, France, Germany, Austria, Belgium, and the Netherlands, featuring robust multilingual conversation capture (58 languages). Unifying the Fragmented Desktop The most significant update is the integration of Dragon Copilot with Microsoft 365 Copilot. Historically, clinical data (inside the EHR) and operational data (inside emails, Teams chats, and PDFs) lived in two separate universes. Now, powered by a layer called “Work IQ,” Dragon Copilot can synthesize both. A clinician can naturally query the AI to pull a patient’s lab results, cross-reference them with a new hospital policy document, and check their own schedule—all without toggling between tabs. Furthermore, Microsoft has untethered the AI from a specific interface. By simply clicking or highlighting text across applications, EHRs, or web pages, a clinician can invoke Dragon Copilot. For example, a doctor reviewing a note can hover over a sentence and say, “Add more detail about what the patient shared regarding their cardiac history,” and the AI will contextually expand the documentation right there. No copying, no pasting. The “App Store” for Clinical AI In a brilliant strategic move to solidify its platform dominance, Microsoft is turning Dragon Copilot into a distribution channel for other health-tech companies. Through the Microsoft Marketplace, health systems can now deploy partner-built AI apps and agents directly into the Dragon Copilot workflow. At launch, partners include Canary Speech, Humata Health, Optum, and Regard. “By combining Dragon’s ambient conversation capture with Regard’s ability to surface key insights from data, we expect to help our clinicians identify comorbidities and relevant diagnoses in real time without adding steps to their workflow,” said Dr. Joseph Evans, Vice President and Chief Health Information Officer at Sentara Health. Enabling third parties to build on top of its ambient listening engine, ensures that Microsoft Dragon Copilot isn’t just a documentation tool; it is the central operating system for clinical decision support, revenue cycle management, and prior authorization. Expanding the Footprint: Nurses and Radiologists While early ambient AI was built almost exclusively for primary care physicians, Microsoft is aggressively expanding its footprint across the care team. Nurses: The nursing workflow is notoriously structured and rigid. Dragon Copilot now captures ambient conversations at the bedside and transforms them into highly structured flowsheet entries. With expanded support for med-surg templates and LDAWs (lines, drains, and airways), nurses can document completely hands-free. Radiologists: Currently in preview in the U.S., Dragon Copilot pairs with PowerScribe One to automate routine steps in report creation, specifically summarizing prior radiology reports so the radiologist can focus purely on interpreting the new image.
Google Cloud Showcases Agentic AI Healthcare Partnerships with CVS Health, Humana, and Waystar
What You Should Know The Paradigm Shift: At HIMSS 2026, Google Cloud officially signaled the end of the “point-and-click” software era in healthcare, ushering in the age of “agentic AI”—systems that autonomously execute complex, multi-step workflows. The Infrastructure: These capabilities are powered by Vertex AI and the multimodal Gemini models, operating within a secure, HIPAA-compliant ... Read More
<img loading="lazy" width="1500" height="265" src="https://hitconsultant.net/wp-content/uploads/2025/04/image-15-1500x265.png" alt="Google Cloud and Seattle Children's Partner to Develop AI-Powered 'Pathway Assistant'" class="wp-image-87197" srcset="https://hitconsultant.net/wp-content/uploads/2025/04/image-15-1500x265.png 1500w, https://hitconsultant.net/wp-content/uploads/2025/04/image-15-300x53.png 300w, https://hitconsultant.net/wp-content/uploads/2025/04/image-15-290x51.png 290w, https://hitconsultant.net/wp-content/uploads/2025/04/image-15-768x136.png 768w, https://hitconsultant.net/wp-content/uploads/2025/04/image-15-1536x271.png 1536w, https://hitconsultant.net/wp-content/uploads/2025/04/image-15.png 1920w" sizes="(max-width: 1500px) 100vw, 1500px" /> What You Should Know The Paradigm Shift: At HIMSS 2026, Google Cloud officially signaled the end of the “point-and-click” software era in healthcare, ushering in the age of “agentic AI”—systems that autonomously execute complex, multi-step workflows. The Infrastructure: These capabilities are powered by Vertex AI and the multimodal Gemini models, operating within a secure, HIPAA-compliant “walled garden” that ensures patient data is never used to train Google’s foundation models. CVS Health’s Health100: CVS is launching an open, AI-native consumer engagement platform called Health100, designed to provide proactive health interventions and connect users to pharmacist-led care, regardless of their insurance provider. Massive Hard ROI: Highmark Health expanded its generative AI assistant, Sidekick, delivering a calculated $27.9M in AI-enabled value in 2025 alone. Similarly, revenue cycle giant Waystar utilized Google Cloud’s AI to prevent more than $15 billion in denied claims. Consumer & Member Experience: Humana is deploying Agent Assist to its 20,000 member advocates to summarize calls in real-time, while Quest Diagnostics launched the Quest AI Companion to translate complex lab results into plain language for patients. The Multimodal Advantage To understand why agentic AI is suddenly viable in healthcare, you have to look at the underlying architecture. Google’s Gemini models are natively multimodal. They do not just read text; they can process text from an Electronic Health Record (EHR), analyze voice transcripts from a patient call, and evaluate visual data from a scan simultaneously. By operating within Google Cloud’s “secure-by-default,” HIPAA-compliant infrastructure, these agents function in a walled garden. This allows organizations to deploy powerful AI without compromising data residency or feeding proprietary clinical data back into public foundation models. From Ecosystems to Autonomous Revenue The announcements at HIMSS prove that agentic AI is no longer trapped in pilot purgatory; it is operating at hyperscale. CVS Health is making an ambitious consumer play with the launch of Health100. Backed by Gemini, this tech-enabled subsidiary is building an open, AI-native consumer engagement platform. Unlike traditional payer apps, Health100 is designed to ingest data from wearables and health records to provide real-time, proactive support—essentially functioning as an always-on personal healthcare partner that eliminates the “homework” of navigating the medical system. On the provider operations side, the numbers are staggering. Highmark Health has scaled its internal generative AI assistant, Sidekick, to handle over 6 million prompts across 74 active use cases. By automating research protocols, creating synthetic focus groups, and serving as an AI search proxy, Sidekick delivered an estimated $27.9 million in value in 2025 alone. Similarly, Waystar is using Google’s infrastructure to pioneer the autonomous revenue cycle. By embedding agentic AI directly into the claims lifecycle, Waystar AltitudeAI has already prevented more than $15 billion in denied claims in less than a year, reducing the time spent on denial appeals by 90%. Restoring the Human Element Ironically, the ultimate goal of deploying artificial intelligence in healthcare is to make the experience more human. – Humana is demonstrating this by deploying Agent Assist to its 20,000 member advocates. Handling 80 million calls annually, these advocates previously spent the majority of their time frantically searching through policy documents. Now, the AI summarizes the conversation in real-time and surfaces the exact benefit details needed, allowing the human advocate to actually listen to and empathize with the caller. – Quest Diagnostics is applying a similar philosophy directly to the patient. Their new Quest AI Companion, integrated into the MyQuest app, allows patients to chat with their lab results. Instead of staring blankly at a high lipid panel, the patient receives a plain-language explanation of their biomarkers and a suggested list of questions to ask their doctor.
Sage Raises $65M to Expand AI Senior Care Platform to Prevent Falls
What You Should Know The Funding: Sage, an integrated care platform for senior living and skilled nursing, has raised a $65M Series C led by Growth Equity at Goldman Sachs Alternatives, bringing its total capital to $124M. The Market Crisis: The senior care industry is currently short 1.8 million licensed caregivers and suffers from a ... Read More
<img loading="lazy" width="1500" height="502" src="https://hitconsultant.net/wp-content/uploads/2026/03/Sage_Logo-1500x502.jpg" alt="Sage Raises $65M to Expand AI Senior Care Platform" class="wp-image-94977" srcset="https://hitconsultant.net/wp-content/uploads/2026/03/Sage_Logo-1500x502.jpg 1500w, https://hitconsultant.net/wp-content/uploads/2026/03/Sage_Logo-300x100.jpg 300w, https://hitconsultant.net/wp-content/uploads/2026/03/Sage_Logo-290x97.jpg 290w, https://hitconsultant.net/wp-content/uploads/2026/03/Sage_Logo-768x257.jpg 768w, https://hitconsultant.net/wp-content/uploads/2026/03/Sage_Logo-1536x514.jpg 1536w, https://hitconsultant.net/wp-content/uploads/2026/03/Sage_Logo-2048x685.jpg 2048w" sizes="(max-width: 1500px) 100vw, 1500px" /> What You Should Know The Funding: Sage, an integrated care platform for senior living and skilled nursing, has raised a $65M Series C led by Growth Equity at Goldman Sachs Alternatives, bringing its total capital to $124M. The Market Crisis: The senior care industry is currently short 1.8 million licensed caregivers and suffers from a staggering 79% turnover rate. Meanwhile, 72 million Americans will reach retirement age by 2030. The Tech Solution: Sage is deploying predictive AI to shift the industry from a reactive posture to a preventative one. Its Sage Detect engine analyzes daily activity patterns (like sleep changes and bathroom frequency) to identify fall risks before adverse events occur. The Workflow Integration: Sage unifies data from fragmented Electronic Health Records (EHRs)—including PointClickCare, Yardi, ALIS, and ECP—into a single, real-time dashboard, vastly reducing the cognitive load on caregivers. The Hard ROI: Sage-powered communities are already reporting a $275 increase in Net Operating Income (NOI) per resident per month, a 50% reduction in falls, and 50% faster response times. The $65M Pivot to Prevention: How Sage is Using AI to Rewire Senior Care By 2030, one in five Americans will be of retirement age, yet the caregiving workforce is fundamentally unequipped to handle the surge. The industry is short 1.8 million licensed caregivers, and the ones currently working are burning out at a staggering 79% turnover rate.We cannot simply hire our way out of this crisis. We have to fundamentally rewire how caregivers operate. Today, Sage announced a massive $65M Series C funding round led by Growth Equity at Goldman Sachs Alternatives to do exactly that. The company is actively replacing the fragmented, paper-and-pager infrastructure of skilled nursing and senior living facilities with an AI-powered operating system designed to predict medical crises before they happen. “Every caregiver I talk to says the same thing: current tools are not built for how care actually works, contributing to chaotic environments that fail both caregivers and residents,” said Raj Mehra, Co-founder and CEO of Sage. Sage Detect: From Reaction to Prediction Historically, the technology used in senior care has been strictly reactive. Caregivers are alerted after a resident has fallen, after a condition has severely deteriorated, or after an ambulance has been called. Sage is utilizing its new capital to accelerate the deployment of Sage Detect, its AI-driven predictive engine. Instead of waiting for an emergency pull-cord to be yanked, the software analyzes subtle daily activity patterns. By tracking leading indicators such as sleep disruptions, nighttime wandering, and increased bathroom frequency, Sage can flag high-risk residents to the care team, providing the crucial lead time needed to intervene and prevent an adverse event. According to the company, this proactive model reduces falls by 50% and improves caregiver response times by 50% compared to the industry average. Unifying the Caregiver Workflow Predictive analytics are useless if the data is buried in a clunky software interface. In most senior living communities, caregivers are forced to toggle between multiple, disconnected systems to piece together a single resident’s health status. To solve this, Sage acts as a central nervous system. It pulls data directly from leading Electronic Health Records (EHRs)—including ALIS, August Health, ECP, PointClickCare, and Yardi—into one unified, real-time care view. This streamlined workflow is particularly vital for skilled nursing facilities, which operate under some of the most demanding clinical and regulatory conditions in healthcare. Sage drastically reduces the cognitive load on an already overwhelmed workforce by surfacing alerts, risk signals, and resident-specific context exactly at the point of care. “This investment allows us to put caregivers at the center of innovation — by delivering a platform that provides real-time intelligence, and by convening an inaugural summit to ensure their voices and expertise drive the future of the industry,” noted Raj Mehra, co-founder and CEO of Sage.
Health Recovery Solutions (HRS) Acquires Rimidi for Chronic Care Management and RPM Integration
What You Should Know The Acquisition: Health Recovery Solutions (HRS), a dominant player in remote patient monitoring (RPM) and enterprise remote care, has officially acquired Rimidi, an Atlanta-based chronic disease management company. Financial details were not disclosed. The Strategic Shift: The deal accelerates HRS’s transition from a primarily post-acute monitoring company into a comprehensive, end-to-end ... Read More
<img loading="lazy" width="1500" height="492" src="https://hitconsultant.net/wp-content/uploads/2026/03/Health-Recovery-Solutions-HRS-Acquires-Rimidi-for-Chronic-Care-Management-and-RPM-Integration-1500x492.webp" alt="" class="wp-image-94974" srcset="https://hitconsultant.net/wp-content/uploads/2026/03/Health-Recovery-Solutions-HRS-Acquires-Rimidi-for-Chronic-Care-Management-and-RPM-Integration-1500x492.webp 1500w, https://hitconsultant.net/wp-content/uploads/2026/03/Health-Recovery-Solutions-HRS-Acquires-Rimidi-for-Chronic-Care-Management-and-RPM-Integration-300x98.webp 300w, https://hitconsultant.net/wp-content/uploads/2026/03/Health-Recovery-Solutions-HRS-Acquires-Rimidi-for-Chronic-Care-Management-and-RPM-Integration-290x95.webp 290w, https://hitconsultant.net/wp-content/uploads/2026/03/Health-Recovery-Solutions-HRS-Acquires-Rimidi-for-Chronic-Care-Management-and-RPM-Integration-768x252.webp 768w, https://hitconsultant.net/wp-content/uploads/2026/03/Health-Recovery-Solutions-HRS-Acquires-Rimidi-for-Chronic-Care-Management-and-RPM-Integration-1536x504.webp 1536w, https://hitconsultant.net/wp-content/uploads/2026/03/Health-Recovery-Solutions-HRS-Acquires-Rimidi-for-Chronic-Care-Management-and-RPM-Integration.webp 1599w" sizes="(max-width: 1500px) 100vw, 1500px" /> What You Should Know The Acquisition: Health Recovery Solutions (HRS), a dominant player in remote patient monitoring (RPM) and enterprise remote care, has officially acquired Rimidi, an Atlanta-based chronic disease management company. Financial details were not disclosed. The Strategic Shift: The deal accelerates HRS’s transition from a primarily post-acute monitoring company into a comprehensive, end-to-end longitudinal care provider. It bolsters the “PatientFirst Pathways” care model HRS introduced in 2025. The Clinical Payload: Rimidi brings deep expertise in the ambulatory setting, specifically targeting diabetes and cardiometabolic management. This includes advanced integration capabilities with major Continuous Glucose Monitoring (CGM) devices like Dexcom, FreeStyle Libre, and Eversense directly into the EHR workflow. The Leadership Move: As part of the acquisition, Rimidi’s CEO and Founder, Dr. Lucienne Ide, will step into the role of Chief Medical Officer for HRS, signaling a heavy emphasis on clinical rigor and outcomes over pure software deployment. The ROI Focus: Rimidi’s platform has a proven track record of reducing the total cost of care, with one healthcare partner achieving an average 2.8% reduction in hemoglobin A1c levels and driving meaningful reductions in hospitalizations for high-risk type 2 diabetes patients. Merging the Post-Acute with the Ambulatory HRS has spent over a decade dominating the post-acute and hospital-at-home sectors. With over one million patients monitored to date, their infrastructure is built to handle complex operational logistics and high-acuity interventions. Rimidi, on the other hand, was built by doctors, for doctors, to thrive in the ambulatory (outpatient) setting. The platform excels at ingesting continuous clinical data and transforming it into actionable insights for primary and specialty care clinics. By bolting Rimidi onto its existing architecture, HRS is bridging the gap between acute recovery and everyday life. “HRS’s leadership in enterprise remote patient care and dedication to quality perfectly complement the mission Rimidi was founded on. By integrating Rimidi’s extensive experience and capabilities in ambulatory disease management into their comprehensive platform, we can jointly support the entire patient journey across care settings, clinical conditions, and levels of patient acuity. Our combined solutions will enhance the reach and effectiveness of HRS’s already high‑value offerings, amplifying the positive impact we can make on patient outcomes,” noted Dr. Lucienne Ide, CEO and Founder of Rimidi, who will now serve as Chief Medical Officer for HRS. The Continuous Glucose Monitoring (CGM) Catalyst One of the most valuable assets HRS acquires in this deal is Rimidi’s sophisticated integration with Continuous Glucose Monitors (CGMs). Driven by expanding insurance coverage, the CGM market is exploding. However, simply handing a patient a Dexcom or a FreeStyle Libre does not improve care if the resulting data is not actionable for the physician. Rimidi aggregates massive streams of data from leading CGM devices and pipes those glucose insights directly into the clinician’s existing Electronic Health Record (EHR) workflow. The integration of Rimidi’s specialized diabetes management capability with HRS’s robust operational scale will enable health systems to standardize how they monitor their costliest chronic populations. “HRS is committed to expanding enterprise remote patient care to meet evolving customer needs,” said Jason Comer, CEO of HRS. “With our recent introduction of PatientFirst Pathways and expansion into Chronic Care Management, this acquisition enhances our ability to deliver comprehensive longitudinal care. Rimidi’s clinical workflow expertise, deep roots in diabetes management, and strong track record of improving patient outcomes make them an ideal addition.”
Using Clinical NLP to Unlock Untapped Quality Data for HEDIS Compliance
Tim O 'Connell, M.ENG, M.D, Co-Founder CEO at emtelligent
From my experience working with healthcare providers and payers, there’s one thing that stands out to me: the most important insights for compliance are almost never in the data fields you expect. Instead, they’re buried somewhere in the mounds of clinical data amassing in healthcare every day. As a practicing radiologist, I see firsthand just ... Read More
<img loading="lazy" src="https://hitconsultant.net/wp-content/uploads/2026/03/TimOConnell_emtelligent_Headshot-1500x1762.jpg" alt="Using Clinical NLP to Unlock Untapped Quality Data for HEDIS Compliance " class="wp-image-94875" width="520" height="611" srcset="https://hitconsultant.net/wp-content/uploads/2026/03/TimOConnell_emtelligent_Headshot-1500x1762.jpg 1500w, https://hitconsultant.net/wp-content/uploads/2026/03/TimOConnell_emtelligent_Headshot-255x300.jpg 255w, https://hitconsultant.net/wp-content/uploads/2026/03/TimOConnell_emtelligent_Headshot-247x290.jpg 247w, https://hitconsultant.net/wp-content/uploads/2026/03/TimOConnell_emtelligent_Headshot-768x902.jpg 768w, https://hitconsultant.net/wp-content/uploads/2026/03/TimOConnell_emtelligent_Headshot-1308x1536.jpg 1308w, https://hitconsultant.net/wp-content/uploads/2026/03/TimOConnell_emtelligent_Headshot-1744x2048.jpg 1744w" sizes="(max-width: 520px) 100vw, 520px" /> Tim O’Connell, M.ENG, M.D, Co-Founder & CEO at emtelligent From my experience working with healthcare providers and payers, there’s one thing that stands out to me: the most important insights for compliance are almost never in the data fields you expect. Instead, they’re buried somewhere in the mounds of clinical data amassing in healthcare every day. As a practicing radiologist, I see firsthand just how much of the most meaningful information never makes it into traditional reporting. In my experience working with payers and providers, the difference between missing reporting targets and exceeding them usually comes down to how well you can access what’s hidden in the rising mountains of clinical narrative. I’ve also found that with the help of natural language processing (NLP), it’s entirely possible to find every needle in the haystack and consistently exceed reporting requirements. The Unstructured Data Gap is Too Wide to Cross Alone More than 80% of healthcare data is unstructured, meaning it exists as physicians notes, referrals, discharge summaries, radiology images, and other documents in a patient’s electronic health record that defy organization by pre-defined structure. That leaves just 20% of health data able to fit into neatly structured fields. Most of the time, the details that matter for HEDIS and accreditation are locked away within this narrative text. That can make it tempting to focus on easy-to-use structured data. But relying on structured data alone is like reading every fifth page of a book. You miss the context, the crucial facts, and sometimes the entire plot. I’ve watched health plans miss out on better HEDIS scores, risk their accreditation, and lose millions of dollars in revenue due to decreased Star Ratings, all because their systems couldn’t see, and report on, the whole story. Medical NLP is Like a Bridge to Access Unstructured Data Medical NLP has the potential to change everything. That’s because it can extract the exact needed details from thousands of pages of notes without the time-consuming manual labor – which is not just slow, it’s financially crushing. Medical NLP transforms HEDIS from a labor-intensive, retrospective fire-drill costing millions in temporary staffing to a continuous, automated process that minimizes annual expenditures. That’s not just a theory or a dream. It’s already happening. A recent peer-reviewed study of clincial NLP found that 81% were using NLP for data collection, and that in multiple cases, it achieved 90% of higher accuracy in information extraction and classification. That accuracy stems from NLP being much more than a keyword search that misses out on context and relationships. Modern NLP understands language, chronology, negation, and nuance, making it possible to find the evidence needed for HEDIS measures, accurately codify events, and create a trail that auditors can follow. That means more complete quality reporting, fewer missed care gaps, and data that holds up under scrutiny. That’s more than just excellent compliance. It’s trust in the making. How to Use NLP to Build a HEDIS-Ready Data Pipeline Having an excellent NLP engine isn’t enough on its own. The organizations that have the most success with HEDIS compliance are the ones that think strategically about their entire data pipeline from start to finish. It’s not just about analytics; it’s about being audit-ready all the time. That means developing architecture that can bring together and make meaning of both structured and unstructured data, building in transparency from the beginning, and making sure that every insight can be traced back to the source. The goal is to create a foundation where technology simultaneously support the people doing the work while reducing manual effort and helps to improve outcomes without introducing or perpetuating information black boxes. The Positive Impact of NLP on Business and Compliance When— not if— you get this right, the results are real and immediate: better HEDIS scores, stronger Star Ratings, and the ability to maintain accreditation and financial performance without it always feeling like a struggle. Investing in explainable, auditable data pipelines will prepare you for not just today’s requirements, but for every change that comes. Unlocking the full value of unstructured clinical data isn’t just a technical problem, it’s a strategic one. Taking the extraction and analysis of unstructured data seriously and using NLP to your advantage in pulling out buried insights will position your organization to excel in compliance, audit, and care quality without increasing your work burdens. About Dr. Tim O’Connell Dr. Tim O’Connell is the founder and CEO of emtelligent, a clinical-grade AI solution. He is also a practicing radiologist and the vice-chair of clinical informatics at the University of British Columbia.
Greater Good Health Raises $20.5M to Expand Value-Based Primary Care Clinics
What You Should Know The Funding: Greater Good Health has secured a $20.5M Series B led by Allumia Ventures, alongside up to $12.5M in venture debt from HSBC Innovation Banking. The Backers: The round features strategic participation from heavy hitters, including DaVita Venture Group, Granite Financial Holdings (the investment arm of Blue Cross of Idaho), ... Read More
<img loading="lazy" width="1500" height="1257" src="https://hitconsultant.net/wp-content/uploads/2026/03/GreaterGoodHealth_leadership_team-1500x1257.jpg" alt="Greater Good Health Raises $20.5M to Expand Value-Based Primary Care Clinics" class="wp-image-94982" srcset="https://hitconsultant.net/wp-content/uploads/2026/03/GreaterGoodHealth_leadership_team-1500x1257.jpg 1500w, https://hitconsultant.net/wp-content/uploads/2026/03/GreaterGoodHealth_leadership_team-300x251.jpg 300w, https://hitconsultant.net/wp-content/uploads/2026/03/GreaterGoodHealth_leadership_team-290x243.jpg 290w, https://hitconsultant.net/wp-content/uploads/2026/03/GreaterGoodHealth_leadership_team-768x644.jpg 768w, https://hitconsultant.net/wp-content/uploads/2026/03/GreaterGoodHealth_leadership_team-1536x1288.jpg 1536w, https://hitconsultant.net/wp-content/uploads/2026/03/GreaterGoodHealth_leadership_team-2048x1717.jpg 2048w" sizes="(max-width: 1500px) 100vw, 1500px" /> Greater Good Health Executive Team: Sylvia Hastanan (CEO/Founder), Matt Gagalis (CCO), Mike Grover (CFO) and Tyler Jung, MD (CMO) What You Should Know The Funding: Greater Good Health has secured a $20.5M Series B led by Allumia Ventures, alongside up to $12.5M in venture debt from HSBC Innovation Banking. The Backers: The round features strategic participation from heavy hitters, including DaVita Venture Group, Granite Financial Holdings (the investment arm of Blue Cross of Idaho), Optum Ventures, and Flare Capital Partners. The Model: The company tackles the primary care physician shortage by deploying a Nurse Practitioner (NP)-centric care model, designed to manage complex Medicare populations through proactive, value-based care arrangements. The Scale: Operating as an extension of health plans and hospital systems, Greater Good Health currently serves more than 200,000 patients. They recently opened their fourth physical clinic—and first in Idaho—partnering directly with Blue Cross of Idaho. The ROI: The model is yielding hard clinical outcomes, including 4+ STAR quality performance, a 200% increase in preventive care engagement, and meaningful reductions in unnecessary acute hospital admissions. The NP-Centric Care Model For decades, the traditional primary care model has struggled to keep pace, both clinically and financially. In rural and underserved markets, the physician shortage isn’t a future projection; it is a current, operational reality. Operating either alongside existing primary care infrastructure or serving directly as the primary care home, Greater Good Health deploys an NP-centric model engineered specifically for value-based care arrangements. Nurse practitioners are highly trained to manage chronic conditions, focus on holistic well-being, and spend the necessary time with complex patients—preventative actions that ultimately drive down downstream medical spend. “Healthcare is facing two very real challenges at the same time – a growing shortage of physicians and medical costs that continue to rise faster than outcomes,” said Sylvia Hastanan, Founder and CEO of Greater Good Health. “By empowering nurse practitioners to lead care teams, we have built a proven care model that manages complex populations proactively and cost effectively.” Great Good VBC Primary Care Model ROI In the digital health and tech-enabled services sector, raising a Series B requires more than a compelling narrative; it requires hard unit economics. Greater Good Health is delivering on the metrics that matter most to its strategic partners, which already include health plan giants like Humana and Blue Cross of Idaho. Currently serving more than 200,000 patients, the company has demonstrated: 4+ STAR quality performance ratings Over 200% growth in preventive care engagement Meaningful reductions in unnecessary acute hospital admissions A patient Net Promoter Score (NPS) above 90 While many health-tech startups try to solve the access problem purely through telehealth algorithms, Greater Good Health recognizes that managing high-risk Medicare populations still requires a localized, physical footprint. The company recently opened its fourth primary care clinic (and its first in Idaho), adding to its existing footprint in Montana. “The ongoing physician shortage remains one of the biggest challenges for our healthcare industry,” said Branden Fini, Partner at Allumia Ventures. “Greater Good Health’s approach to empowering nurse practitioners to deliver high-quality value-based care is an innovative and successful approach to solving the problem. We believe deeply in Greater Good Health’s mission and are proud to support the team as they transform healthcare.”